JGromacs: A Java Package for Analyzing Protein Simulations

In this paper, we introduce JGromacs, a Java API (Application Programming Interface) that facilitates the development of cross-platform data analysis applications for Molecular Dynamics (MD) simulations. The API supports parsing and writing file formats applied by GROMACS (GROningen MAchine for Chemical Simulations), one of the most widely used MD simulation packages. JGromacs builds on the strengths of object-oriented programming in Java by providing a multilevel object-oriented representation of simulation data to integrate and interconvert sequence, structure, and dynamics information. The easy-to-learn, easy-to-use, and easy-to-extend framework is intended to simplify and accelerate the implementation and development of complex data analysis algorithms. Furthermore, a basic analysis toolkit is included in the package. The programmer is also provided with simple tools (e.g., XML-based configuration) to create applications with a user interface resembling the command-line interface of GROMACS applications. <b>Availability:</b> JGromacs and detailed documentation is freely available from http://sbcb.bioch.ox.ac.uk/jgromacs under a GPLv3 license

Steered Molecular Dynamics Simulations Predict Conformational Stability of Glutamate Receptors

The stability of protein–protein interfaces can be essential for protein function. For ionotropic glutamate receptors, a family of ligand-gated ion channels vital for normal function of the central nervous system, such an interface exists between the extracellular ligand binding domains (LBDs). In the full-length protein, the LBDs are arranged as a dimer of dimers. Agonist binding to the LBDs opens the ion channel, and briefly after activation the receptor desensitizes. Several residues at the LBD dimer interface are known to modulate desensitization, and conformational changes around these residues are believed to be involved in the state transition. The general hypothesis is that the interface is disrupted upon desensitization, and structural evidence suggests that the disruption might be substantial. However, when cross-linking the central part of this interface, functional data suggest that the receptor can still undergo desensitization, contradicting the hypothesis of major interface disruption. Here, we illustrate how opening the dimer interface using steered molecular dynamics (SMD) simulations, and analyzing the work values required, provides a quantitative measure for interface stability. For one subtype of glutamate receptors, which is regulated by ion binding to the dimer interface, we show that opening the interface without ions bound requires less work than with ions present, suggesting that ion binding indeed stabilizes the interface. Likewise, for interface mutants with longer-lived active states, the interface is more stable, while the work required to open the interface is reduced for less active mutants. Moreover, a cross-linked mutant can still undergo initial interface opening motions similar to the native receptor and at similar energetic cost. Thus, our results support that interface opening is involved in desensitization. Furthermore, they provide reconciliation of apparently opposing data and demonstrate that SMD simulations can give relevant biological insight into longer time scale processes without the need for expensive calculations

JGromacs: A Java Package for Analyzing Protein Simulations

In this paper, we introduce JGromacs, a Java API (Application Programming Interface) that facilitates the development of cross-platform data analysis applications for Molecular Dynamics (MD) simulations. The API supports parsing and writing file formats applied by GROMACS (GROningen MAchine for Chemical Simulations), one of the most widely used MD simulation packages. JGromacs builds on the strengths of object-oriented programming in Java by providing a multilevel object-oriented representation of simulation data to integrate and interconvert sequence, structure, and dynamics information. The easy-to-learn, easy-to-use, and easy-to-extend framework is intended to simplify and accelerate the implementation and development of complex data analysis algorithms. Furthermore, a basic analysis toolkit is included in the package. The programmer is also provided with simple tools (e.g., XML-based configuration) to create applications with a user interface resembling the command-line interface of GROMACS applications. <b>Availability:</b> JGromacs and detailed documentation is freely available from http://sbcb.bioch.ox.ac.uk/jgromacs under a GPLv3 license

Conformational Preferences of a 14-Residue Fibrillogenic Peptide from Acetylcholinesterase

A 14-residue fragment from near the C-terminus of the enzyme acetylcholinesterase (AChE) is believed to have a neurotoxic/neurotrophic effect acting via an unknown pathway. While the peptide is α-helical in the full-length enzyme, the structure and association mechanism of the fragment are unknown. Using multiple molecular dynamics simulations, starting from a tetrameric complex of the association domain of AChE and systematically disassembled subsets that include the peptide fragment, we show that the fragment is incapable of retaining its helicity in solution. Extensive replica exchange Monte Carlo folding and unfolding simulations in implicit solvent with capped and uncapped termini failed to converge to any consistent cluster of structures, suggesting that the fragment remains largely unstructured in solution under the conditions considered. Furthermore, extended molecular dynamics simulations of two steric zipper models show that the peptide is likely to form a zipper with antiparallel sheets and that peptides with mutations known to prevent fibril formation likely do so by interfering with this packing. The results demonstrate how the local environment of a peptide can stabilize a particular conformation

Example screenshots from (A) Starting submission screen, (B) multiple-sequence alignment for P2X proteins and (C) detailed information screen from a mutation found for the P2X7 protein.

<p>Example screenshots from (A) Starting submission screen, (B) multiple-sequence alignment for P2X proteins and (C) detailed information screen from a mutation found for the P2X7 protein.</p

Information retrieval and mutation extraction in three test cases.

*<p>These are the keywords that MutationMapper automatically extracted from Uniprot and used to search PubMed.</p

JGromacs: A Java Package for Analyzing Protein Simulations

In this paper, we introduce JGromacs, a Java API (Application Programming Interface) that facilitates the development of cross-platform data analysis applications for Molecular Dynamics (MD) simulations. The API supports parsing and writing file formats applied by GROMACS (GROningen MAchine for Chemical Simulations), one of the most widely used MD simulation packages. JGromacs builds on the strengths of object-oriented programming in Java by providing a multilevel object-oriented representation of simulation data to integrate and interconvert sequence, structure, and dynamics information. The easy-to-learn, easy-to-use, and easy-to-extend framework is intended to simplify and accelerate the implementation and development of complex data analysis algorithms. Furthermore, a basic analysis toolkit is included in the package. The programmer is also provided with simple tools (e.g., XML-based configuration) to create applications with a user interface resembling the command-line interface of GROMACS applications. <b>Availability:</b> JGromacs and detailed documentation is freely available from http://sbcb.bioch.ox.ac.uk/jgromacs under a GPLv3 license

Quantifying Water-Mediated Protein–Ligand Interactions in a Glutamate Receptor: A DFT Study

It is becoming increasingly clear that careful treatment of water molecules in ligand–protein interactions is required in many cases if the correct binding pose is to be identified in molecular docking. Water can form complex bridging networks and can play a critical role in dictating the binding mode of ligands. A particularly striking example of this can be found in the ionotropic glutamate receptors. Despite possessing similar chemical moieties, crystal structures of glutamate and α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) in complex with the ligand-binding core of the GluA2 ionotropic glutamate receptor revealed, contrary to all expectation, two distinct modes of binding. The difference appears to be related to the position of water molecules within the binding pocket. However, it is unclear exactly what governs the preference for water molecules to occupy a particular site in any one binding mode. In this work we use density functional theory (DFT) calculations to investigate the interaction energies and polarization effects of the various components of the binding pocket. Our results show (i) the energetics of a key water molecule are more favorable for the site found in the glutamate-bound mode compared to the alternative site observed in the AMPA-bound mode, (ii) polarization effects are important for glutamate but less so for AMPA, (iii) ligand–system interaction energies alone can predict the correct binding mode for glutamate, but for AMPA alternative modes of binding have similar interaction energies, and (iv) the internal energy is a significant factor for AMPA but not for glutamate. We discuss the results within the broader context of rational drug-design

Mean dRMSD dissimilarity between the ligand-bound conformations and the most similar, 10 most similar, 100 most similar and 200 most similar snapshots of the apo MD simulations (for details of the Q(1), Q(10), Q(100) and Q(200) measures see Methods).

<p>Mean dRMSD dissimilarity between the ligand-bound conformations and the most similar, 10 most similar, 100 most similar and 200 most similar snapshots of the apo MD simulations (for details of the Q(1), Q(10), Q(100) and Q(200) measures see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002749#s3" target="_blank">Methods</a>).</p

Multidimensional scaling analysis for Dvl2 PDZ colored by silhouette index values (A) and by cluster membership (B).

<p>Blue dots represent conformations that belong to cluster one; red dots those that belong to cluster two. The four crystal structures, pep-C1, pep-N1, pep-N2 and pep-N3 are represented by magenta, cyan, yellow and green dots, respectively. A comparison of the medoid conformation from cluster one to experimentally observed ligand-bound states (C) shows that medoid (blue) is closer to the conformation for pep-N3 (red) than pep-N2 (green). Conversely, the medoid conformation from cluster two (D) is closer to the conformation of pep-N2 (green) than pep-N3 (red). Multidimensional scaling analysis for the Erbin PDZ (E) reveals one major cluster (blue dots) with several outliers (red dots) defined as conformations that have dRMSD dissimilarity equal or larger than 0.8 Å from the medoid conformer.</p